Details of forecast revisions from news, organized by impacts first
Index is as MultiIndex consisting of:
impact date: the date of the impact on the variable of interest
impacted variable: the variable that is being impacted
update date: the date of the data update, that results in news that impacts the forecast of variables of interest
updated variable: the variable being updated, that results in news that impacts the forecast of variables of interest
The columns are:
forecast (prev): the previous forecast of the new entry, based on the information available in the previous dataset
observed: the value of the new entry, as it is observed in the new dataset
news: the news associated with the update (this is just the forecast error: observed - forecast (prev))
weight: the weight describing how the news effects the forecast of the variable of interest
impact: the impact of the news on the forecast of the variable of interest
This table decomposes updated forecasts of variables of interest from the news associated with each updated datapoint from the new data release.
This table does not summarize the impacts or show the effect of revisions. That information can be found in the impacts table.
This form of the details table is organized so that the impacted dates / variables are first in the index. This is convenient for slicing by impacted variables / dates to view the details of data updates for a particular variable or date.
However, since the forecast (prev) and observed columns have a lot of duplication, printing the entire table gives a result that is less easy to parse than that produced by the details_by_update property. details_by_update contains the same information but is organized to be more convenient for displaying the entire table of detailed updates. At the same time, details_by_update is less convenient for subsetting.